Screening of the Antagonistic Activity of Potential Bisphenol A Alternatives toward the Androgen Receptor Using Machine Learning and Molecular Dynamics Simulation.

Over the past few decades, extensive research has indicated that exposure to bisphenol A (BPA) increases the health risks in humans. Toxicological studies have demonstrated that BPA can bind to the androgen receptor (AR), resulting in endocrine-disrupting effects. In recent investigations, many alternatives to BPA have been detected in various environmental media as major pollutants. However, related experimental evaluations of BPA alternatives have not been systematically implemented for the assessment of chemical safety and the effects of structural characteristics on the antagonistic activity of the AR. To promote the green development of BPA alternatives, high-throughput toxicological screening is fundamental for prioritizing chemical tests. Therefore, we proposed a hybrid deep learning architecture that combines molecular descriptors and molecular graphs to predict AR antagonistic activity. Compared to previous models, this hybrid architecture can extract substantial chemical information from various molecular representations to improve the model's generalization ability for BPA alternatives. Our predictions suggest that lignin-derivable bisguaiacols, as alternatives to BPA, are likely to be nonantagonist for AR compared to bisphenol analogues. Additionally, molecular dynamics (MD) simulations identified the dihydrotestosterone-bound pocket, rather than the surface, as the major binding site of bisphenol analogues. The conformational changes of key helix H12 from an agonistic to an antagonistic conformation can be evaluated qualitatively by accelerated MD simulations to explain the underlying mechanism. Overall, our computational study is helpful for toxicological screening of BPA alternatives and the design of environmentally friendly BPA alternatives.

NeuTox: A weighted ensemble model for screening potential neuronal cytotoxicity of chemicals based on various types of molecular representations.

Chemical-induced neurotoxicity has been widely brought into focus in the risk assessment of chemical safety. However, the traditional in vivo animal models to evaluate neurotoxicity are time-consuming and expensive, which cannot completely represent the pathophysiology of neurotoxicity in humans. Cytotoxicity to human neuroblastoma cell line (SH-SY5Y) is commonly used as an alternative to animal testing for the assessment of neurotoxicity, yet it is still not appropriate for high throughput screening of potential neuronal cytotoxicity of chemicals. In this study, we constructed an ensemble prediction model, termed NeuTox, by combining multiple machine learning algorithms with molecular representations based on the weighted score of Particle Swarm Optimization. For the test set, NeuTox shows excellent performance with an accuracy of 0.9064, which are superior to the top-performing individual models. The subsequent experimental verifications reveal that 5,5'-isopropylidenedi-2-biphenylol and 4,4'-cyclo-hexylidenebisphenol exhibited stronger SH-SY5Y-based cytotoxicity compared to bisphenol A, suggesting that NeuTox has good generalization ability in the first-tier assessment of neuronal cytotoxicity of BPA analogs. For ease of use, NeuTox is presented as an online web server that can be freely accessed via http://www.iehneutox-predictor.cn/NeuToxPredict/Predict.

Therapeutic effect of Eleutherococcus senticosus (Rupr. & Maxim.) Maxim. leaves on ischemic stroke via the microbiota-gut-brain axis.

Eleutherococcus senticosus (Rupr. & Maxim.) Maxim. leaves (ESL) are widely used to treat ischemic stroke (IS); however, the specific mechanism remains unclear. The microbiota-gut-brain axis plays a critical role in IS and has become a potential therapeutic target. This study aimed to reveal and verify the therapeutic effect of ESL on IS through the microbiota-gut-brain axis. Ultra-high-performance liquid chromatography coupled with mass spectrometry-based untargeted/targeted metabolomics combined with 16S rRNA microbiota sequencing strategy were used to investigate the regulatory effect of ESL on the metabolism and intestinal microenvironment after IS. Lactobacillus reuteri and Clostridium butyricum were used to treat rats with IS to verify that elevated levels of probiotics are key factors in the therapeutic effect of ESL. The results showed that IS significantly altered the accumulation of 41 biomarkers, while ESL restored their concentrations back to normal. Moreover, ESL alleviated the dysbiosis of gut microbiota brought on by IS, by reducing the abundance of pathogens and increasing the abundance of probiotics (e.g., Lactobacillus reuteri and Clostridium butyricum); this could reduce post-stroke injury, thereby having a certain protective effect on IS. This study reveals that ESL plays an important role in treating IS through the microbiota-gut-brain axis, maintaining metabolic homeostasis in vivo.

Effects of Various Valence Ions on an Aqueous Rechargeable Zn//Polyaniline-coated ZnMn2 O4 Battery.

Zinc corrosion and dendrite formation are the main issues which impede the performance of aqueous zinc ion batteries (ZIBs) after certain times. In this work, we systematically investigated the effects of three different valence ions (e. g., Na+ , Mg2+ , Al3+ ) as electrolyte additives on the suppression of zinc corrosion and the inhibition of dendrite growth. By combining experiments and theoretical calculations, it has been found that the existence of Na+ ions effectively suppressing the zinc dendrite growth because Na+ possessess high adsorption energy approximately -0.39 eV. Moreover, Na+ ions could lengthen the zinc dendrite formation duration up to 500 h. On the other hand, the PANI/ZMO cathode materials showed the small band gap approximately 0.097 eV, signifying that the PANI/ZMO possessed the semiconductor characteristics. Furthermore, an assembled Zn//PANI/ZMO/GNP full battery using Na+ ions as electrolyte additive displayed capacity retention of 90.2 % after 500 cycles at 0.2 A g-1 , whereas the capacity retention of the control battery using pure ZnSO4 electrolyte was only 58.2 %. This work could provide a reference for the selection of electrolyte additives in future batteries.

In-depth investigation of the mechanisms of Schisandra chinensis polysaccharide mitigating Alzheimer's disease rat via gut microbiota and feces metabolomics.

Schisandra chinensis (S. chinensis) is an herbal medicine used for the treatment of Alzheimer's disease (AD). The purified polysaccharide fraction, namely SCP2, was previously isolated from S. chinensis crude polysaccharide (SCP) and its structure and in vitro activity were investigated. However, the in vivo activity of SCP2 and its potential mechanism for the treatment of AD have yet to be determined. This study used a combination of microbiomics and metabolomics to comprehensively explore the microbiota and metabolic changes in AD rats under SCP2 intervention, with the aim of elucidating the potential mechanisms of SCP2 in the treatment of AD. SCP2 showed significant therapeutic effects in AD rats, as evidenced by improved learning and memory capacity, reduced neuroinflammation, and restoration of the integrity of the intestinal barrier. Fecal metabolomic and microbiomic analyses revealed that SCP2 significantly modulated 19 endogenous metabolites and reversed gut microbiota disorders in AD rats. Moreover, SCP2 significantly increased the content of short-chain fatty acid (SCFAs) in the AD rats. Correlation analysis showed a significant correlation between gut microbes, metabolites and the content of SCFAs. Collectively, these findings will provide the basis for further development of SCP2.

An integrated study on the comprehensive mechanism of Schisandra chinensis polysaccharides mitigating Alzheimer's disease in rats using a UPLC-Q-TOF-MS based serum and urine metabolomics strategy.

As a well-known traditional Chinese medicine and functional food, Schisandra chinensis (S. chinensis) has been proved to possess excellent neuroprotective effects, and particularly the role of the polysaccharide fraction in neuroprotection has been increasingly emphasized. The aim of this study was to investigate the therapeutic effects and potential mechanism of action of the homogeneous polysaccharide SCP2, isolated and purified from S. chinensis polysaccharide (SCP), on Alzheimer's disease (AD) rats based on a holistic metabolomics approach in serum and urine. The results of the pharmacodynamics study showed that SCP2 significantly improved Aß25-35-induced cognitive dysfunction, improved oxidative damage and reduced Aß deposition in the hippocampus. The holistic metabolomics results of serum and urine showed that the intervention with SCP2 significantly reversed the metabolic profile disorder in AD rats. A total of 40 metabolites (21 serum metabolites and 19 urine metabolites) were identified, which were mainly involved in linoleic acid metabolism, alpha-linolenic acid metabolism and arachidonic acid metabolism. The results obtained in this study will provide new insights into the mechanisms of SCP2 in the treatment of AD and provide a basis for the subsequent structure-activity studies of SCP2.

Investigation of the Binding Fraction of PFAS in Human Plasma and Underlying Mechanisms Based on Machine Learning and Molecular Dynamics Simulation.

More than 7000 per- and polyfluorinated alkyl substances (PFAS) have been documented in the U.S. Environmental Protection Agency's CompTox Chemicals database. These PFAS can be used in a broad range of industrial and consumer applications but may pose potential environmental issues and health risks. However, little is known about emerging PFAS bioaccumulation to assess their chemical safety. This study focuses specifically on the large and high-quality data set of fluorochemicals from the related environmental and pharmaceutical chemicals databases, and machine learning (ML) models were developed for the classification prediction of the unbound fraction of compounds in plasma. A comprehensive evaluation of the ML models shows that the best blending model yields an accuracy of 0.901 for the test set. The predictions suggest that most PFAS (∼92%) have a high binding fraction in plasma. Introduction of alkaline amino groups is likely to reduce the binding affinities of PFAS with plasma proteins. Molecular dynamics simulations indicate a clear distinction between the high and low binding fractions of PFAS. These computational workflows can be used to predict the bioaccumulation of emerging PFAS and are also helpful for the molecular design of PFAS to prevent the release of high-bioaccumulation compounds into the environment.

A multidimensional strategy to rapidly identify the chemical constituents in Shengxian Decoction by using ultra-performance liquid chromatography coupled with ion mobility spectrometry quadrupole time-of-flight mass spectrometry.

As a well-known traditional Chinese medicine formula, the chemical constituents of Shengxian Decoction still remain unclear due to its complexity. In this study, a multidimensional strategy based on ultra-performance liquid chromatography coupled with ion mobility spectrometry quadrupole time-of-flight mass spectrometry and informatics UNIFI platform was applied to achieve rapid and comprehensive identification of the complex composition of Shengxian Decoction. Data-independent acquisition, fast data-directed analysis, and high-definition MSE were used to obtain more and cleaner mass spectrum information. As a result, a total of 120 compounds including 74 saponins, 17 flavonoids, 7 cinnamic acid derivatives, 8 triterpenoids, and 14 others were identified or tentatively characterized by high-resolution molecular mass, fragment ions, and collision cross-section values. Furthermore, high-definition MSE was used to identify six pairs of co-eluting isomers that could not be detected from conventional data-independent acquisition and fast data-directed analysis. This research strategy has a certain potential for the analysis of other compound formulae and lays the foundation for the study of traditional Chinese medicine efficacy.

CdS/WO3 S-scheme heterojunction with improved photocatalytic CO2 reduction activity.

The anthropogenic emission of CO2 in the environment affected our atmosphere, which caused a rapid change in the climate. It needs to reduce the excess CO2 from the environment to maintain sustainability and keep it green. In this work, we have fabricated a CdS decorated WO3 nanocomposite, improving the reduction ability of CO2 into CO and CH4 selectively in visible light. The construction of the heterojunction improved the stability of CdS with WO3. It synergistically resulted in ~7.7 times the higher yield of CO and 2.3 times the higher yield of CH4 than CdS using 20 wt% CdS decorated WO3 nanocomposite in a mixture of N,N-dimethylformamide, triethylamine, and water in a 3:1:1 ratio. The 20 wt% CdS on WO3 nanocomposite has proven an effective and selective photocatalyst with the relative yield of methanol up to four cycles. The nanocomposite photocatalysts were analyzed using instrumental techniques, such as XRD, XPS, HR-TEM, FTIR, TGA-DTA, UV-vis, PL spectroscopy, and PEC analysis.

Exploring the origin of efficient adsorption of poly- and perfluoroalkyl substances in household point-of-use water purifiers: Deep insights from a joint experimental and computational study.

Poly- and perfluoroalkyl substances (PFAS) are harmful chemicals to humans and widely detected in water bodies including tap water. PFAS cannot be efficiently removed from water through conventional treatment processes used in full-scale drinking water treatment plants, posing a latent risk to human health via drinking tap water. Here in-field investigations show that the household point-of-use (POU) water purifiers constituted with coconut shell activated carbon can achieve 21%-99% removal for 14 legacy and emerging PFAS in tap water based on the ratio of influent and effluent. Extensive characterizations combine with chemical analyses demonstrate that physical adsorption based on Van der Waals force can remove 23 PFAS from tap water, wherein the hydrophobicity of PFAS is the crucial factor. Density functional theory calculations together with the quantitative structure-activity relationship model confirm that both topological structures as well as hydrophobicity of PFAS and electrostatic interactions between the strong electronegative F atoms and the adsorbent surface are the most critical factors controlling the PFAS adsorption to activated carbon. Overall, our results offer insights into the molecular mechanisms that enable the adsorption of PFAS in POU filters.

A Case of CD5-Positive Primary Cutaneous Diffuse Large B-Cell Lymphoma, Leg Type Secondary to Chronic Lymphedema.

ABSTRACT: Primary cutaneous lymphoma occurring at the site of lymphedema is a rare complication. A total of 13 cases of primary cutaneous lymphoma associated with chronic lymphedema have been reported in international studies. We reported a case of cutaneous diffuse large B-cell lymphoma (DLBCL) (leg type) secondary to chronic lymphedema of the lower limbs. Histopathology showed hyperkeratosis of epidermis, acanthosis, and significant edema in the superficial dermis, with diffuse mononuclear infiltration in the dermis. Immunohistochemical studies revealed the expression of CD5, CD20, Pax-5, Bcl-2, Bcl-6, MUM-1, c-myc, and Ki-67. Therefore, the diagnosis of cutaneous DLBCL (leg type) was made. The study further confirmed the association between lymphoma and lymphedema. Especially, it showed CD5 expression. CD5-positive DLBCLs is a specific subgroup of DLBCLs, only approximately 10% of DLBCLs express CD5.

Insight into the defluorination ability of per- and polyfluoroalkyl substances based on machine learning and quantum chemical computations.

UV-generated hydrated electrons play a critical role in the defluorination reaction of poly- and perfluoroalkyl substances (PFAS). However, limited experimental data hinder insight into the effects of the structural characteristics of emerging PFAS on their defluorination abilities. Therefore, in this study, we adopted quantity structure-activity relationship models based on machine learning algorithms to develop the predictive models of the relative defluorination ability of PFAS. Five-fold cross-validations were used to perform the hyperparameter tuning of the models, which suggested that the gradient boosting algorithms with PaDEL descriptors as the best model possessed superior predictive performance (R2test = 0.944 and RMSEtest = 0.114). The importance of the descriptor indicated that the electrostatic properties and topological structure of the compounds significantly affected the defluorination ability of the PFAS. For the emerging PFAS the best model showed that most compounds, such as potential alternatives of perfluorooctane sulfonic acid, were recalcitrant to reductive defluorination, whereas perfluoroalkyl ether carboxylic acids had relatively stronger defluorination abilities than perfluorooctanoic acid. The theoretical calculations implied that additional electrons on PFAS could cause molecular deconstruction, such as changes in the dihedral angle involved in the carbon chain, as well as C-F bond and ether C-O bond cleavages. In general, the current computational models could be useful for screening emerging PFAS to assess their defluorination ability for the molecular design of fluorochemical structures.

In silico identification of novel inhibitors targeting the DNA-binding domain of the human estrogen receptor alpha.

The human estrogen receptor alpha (ERα) is an important regulator in breast cancer development and progression. The frequent ERα mutations in the ligand-binding domain (LBD) can increase the resistance of antiestrogen drugs, highlighting the need to develop new drugs to target ERα-positive breast cancer. In this study, we combined molecular docking, molecular dynamics simulations and binding free energy calculations to develop a structure-based virtual screening workflow to identify hit compounds capable of interfering with the recognition of ERα by the specific response element of DNA. A druggable pocket on the DNA binding domain (DBD) of ERα was identified as the potential binding site. The hits binding modes were further analyzed to reveal the structural characteristics of the DBD-inhibitor complexes. The core structure of the lead molecules was synthesized and was found to inhibit the E2-induced cell proliferation in MCF-7 cell lines. These findings provide an insight into the structural basis of ligand-ERα for alternate sites beyond the LBD-based pocket. The core structure proposed in this study could potentially be used as the lead molecule for further rational optimization of the antiestrogen drug structure with stronger binding of DBD and higher activity.

Monitoring AuNP Dynamics in the Blood of a Single Mouse Using Single Particle Inductively Coupled Plasma Mass Spectrometry with an Ultralow-Volume High-Efficiency Introduction System.

Gold nanoparticles (AuNPs) are increasingly being used as diagnostic and therapeutic agents owing to their excellent properties; however, there is not much data available on their dynamics in vivo on a single particle basis in a single mouse. Here, we developed a method for the direct analysis of nanoparticles in trace blood samples based on single particle inductively coupled plasma-mass spectrometry (spICP-MS). A flexible, highly configurable, and precisely controlled sample introduction system was designed by assembling an ultralow-volume autosampler (flow rate in the range of 5-5000 µL/min) and a customized cyclonic spray chamber (transfer efficiency up to 99%). Upon systematic optimization, the detection limit of the nanoparticle size (LODsize) of AuNPs in ultrapure water was 19 nm, and the detection limit of the nanoparticle number concentration (LODNP) was 8 × 104 particle/L. Using a retro-orbital blood sampling method and subsequent dilution, the system was successfully applied to track the dynamic changes in size and concentration for AuNPs in the blood of a single mouse, and the recovery for the blood sample was 111.74%. Furthermore, the concentration of AuNPs in mouse blood reached a peak in a short period of time and, then, gradually decreased. This study provides a promising technique for analyzing and monitoring the size and concentration of nanoparticles in ultralow-volume blood samples with low concentrations, making it a powerful tool for analyzing and understanding the fate of nanoparticles in vivo.

Uniportal thoracoscopic pulmonary lobectomy in the treatment of Lung Cancer.

OBJECTIVE: To investigate the clinical efficacy of uniportal thoracoscopic pulmonary lobectomy in the treatment of lung cancer. METHODS: One hundred and ten patients with lung cancer who were admitted to our hospital from February 2017 to June 2018 were enrolled and they were divided into the control group (55 patients) and observation group (55 patients) according to the random number table method. The patients in the observation group received uniportal thoracoscopic pulmonary lobectomy, and patients in the control group underwent triportal thoracoscopic pulmonary lobectomy. The surgical condition, postoperative pulmonary functions, postoperative complication incidence, and postoperative quality of life were compared between the two groups. RESULTS: The intraoperative blood loss and number of dissected lymph nodes of the observation group were (125.31±12.63) mL and (13.91±2.41) respectively, which were not significantly different with (127.54±13.60) mL and (13.96±2.69) of the control group (P>0.05). The incision length of the observation group was (4.22±0.31) cm, shorter than (6.97±0.42) cm of the control group, the postoperative pain score was (2.87±0.69) points, lower than (4.31±1.09) points of the control group, and the operation time was (195.21±19.42) minutes, longer than (162.68±18.52) min of the control group; the differences were significantly different (P<0.05). The postoperative forced vital capacity (FVC), Maximum Ventilatory Volume (MVV) and Forced Expiratory Volume in 1s (FEV1) in the observation group were (1.90±0.75) L, (54.59±16.03) L/minutes and (1.60±0.53) L respectively, larger than (1.06±0.28) L, (38.41±15.59) L/min and (1.02±0.15) L respectively (P<0.05). The scores of Short Form 36-item Health Survey (SF-36) of patients in the observation group was observed one month after surgery, significantly higher than those in the control group, and the difference was statistically significant (P<0.05). The incidence of complications of the postoperative complication of the observation group was 12.7%, which was not significantly different with 14.5% of the control group (P>0.05). CONCLUSION: Patients who receive uniportal video-assisted thoracoscopic pulmonary lobectomy have milder trauma, which is beneficial to the lung functions and postoperative recovery. Moreover, the number of dissected lymph nodes in uniportal thoracoscopic pulmonary lobectomy is equivalent with that in triportal thoracoscopic pulmonary lobectomy. Hence it is worth clinical promotion.

Fluorescence resonance energy transfer between NH2-NaYF4:Yb,Er/NaYF4@SiO2 upconversion nanoparticles and gold nanoparticles for the detection of glutathione and cadmium ions.

Dual-functional nanosensors based on small molecule regulation can be widely used due to their simplicity, high sensitivity and selectivity. Herein, glutathione (GSH) calibrated dual-functional system for GSH and cadmium ions (Cd2+) detection based on fluorescence resonance energy transfer (FRET) between NH2-NaYF4:Yb,Er/NaYF4@SiO2 upconversion nanoparticles (UCNPs) and gold nanoparticles (AuNPs) is designed. Unmodified AuNPs are easy to aggregate in high-salt solution and thereby quenching the red emission of UCNPs. The presence of GSH prevents the aggregation of AuNPs, so GSH can be detected by the changes in the color of solution and the recovery of red emission of UCNPs. However, Cd2+ can interact with GSH, which makes AuNPs easy to aggregate, resulting in a gradual decrease in red emission of UCNPs. The fluorescence response of the system is linear with the concentrations of GSH and Cd2+ in a wide range of concentrations, with low detection limits of 0.016 µM and 0.059 µM, respectively. Furthermore, the nanosensor demonstrates high selectivity for GSH and Cd2+ detection and can be applied for the detection of GSH in human plasma and Cd2+ in drinking water.

Fluorometric determination of antioxidant capacity in human plasma by using upconversion nanoparticles and an inner filter effect mechanism.

The balance between free oxygen radicals and antioxidant defense systems is usually assessed by an antioxidant capacity assay. A rapid and sensitive antioxidant capacity assay is described here. It is making use of NaYF4:Yb/Er@NaYF4 core-shell upconversion nanoparticles (UCNPs) and potassium permanganate (KMnO4). In this strategy, added KMnO4 reduces the green (540 nm) emission of the UCNPs (under 980 nm photoexcitation) due to an inner filter effect. The antioxidants cysteine, ascorbic acid and glutathione (GSH) reduce the intense purple color of KMnO4 because it is reduced to Mn(II) ion. Hence, the green upconversion fluorescence is restored after the addition of antioxidants. Figures of merit for this assay (for the case of GSH) include a detection limit of 3.3 µM, a detection range that extends from 10 µM to 2.5 mM, and an assay time of a few seconds. The assay was applied to the evaluation of antioxidant capacity in human plasma samples spiked with GSH and gave satisfactory repeatability and specificity. Graphical abstract Schematic presentation of a fluorometric assay based on inner filter effect (IFE) between upconversion nanoparticles (UCNPs) and potassium permanganate (KMnO4) for the determination of antioxidant capacity in human plasma.

Correlation Analysis of Pathways and Operons of Helicobacter pylori Resistance Genes Using Bibliometrics.

BACKGROUND: Helicobacter pylori is a gram-negative bacterium infecting approximately 50% of the world's population. Antibiotic resistance in H. pylori has significantly increased due to the overuse and misuse of common antibiotics. Mutations in the 23S rRNA gene and other H. pylori genetic mutations have been identified as significant drivers in the emergence of resistance. Therefore, there is an urgent need for genetic analysis of H. pylori antibiotic resistance. METHODS: Published H. pylori resistance genes were collected from PubMed websites by bibliometrics. Pathway analysis and operon analysis were performed using the Kyoto Encyclopedia of Genes and Genomes (KEGG), the Database for Annotation, Visualization and Integrated Discovery (DAVID), and Database of prOkaryotic OpeRons (DOOR) databases to investigate pathways and biological functions of resistance genes and statistically discover novel resistance genes. RESULTS: A total of 148 genes were mined from the literature using bibliometrics, and 46 enriched pathways were identified using KEGG. Subsequently, 7 novel resistant genes of H. pylor, including HP0776, HP0192, HP0193, HP0475, HP1057, HP0632, and HP0633, were identified and predicted by functional enrichment analysis of pathways and operons. CONCLUSIONS: The discovery of these novel H. pylori resistance genes is of great significance to treat H. pylori-induced diseases and develop optimal treatment regimens. They also provide theoretical fundamentals for epidemiological prevention and strengthen our understanding of the molecular mechanism of H. pylori resistance to antibiotics.

Computational insights on agonist and antagonist mechanisms of estrogen receptor α induced by bisphenol A analogues.

Structural analogues of bisphenol A (BPA) have become widely used as alternatives in BPA-free products. Most toxicological investigations have focused on the estrogenic activities of these analogues, which have been considered as potential environmental estrogens. However, recent studies revealed that certain BPA analogues could dramatically inhibit the proliferation of breast cancer cells, and exhibited strong anti-estrogenic effects compared with the antagonist 4-hydroxytamoxifen (OHT). Thus, we adopted computational models combining molecular dynamics simulations and binding free energy calculations to explore the underlying molecular basis of BPA analogues binding to estrogen receptor α (ERα). We also evaluated ligand-induced structural rearrangements of ERα at the atomic level. Conformational analyses showed that induced-fit H-bonding recognition by Thr347 was an important factor distinguishing antagonist from agonist BPA analogues. Moreover, antagonists of BPA analogues could indirectly induce the structural reposition of key helix 12 and produce an antagonistic conformation of ERα. Compared with OHT, the binding affinity of BPA analogues is stronger for antagonists than agonists. Taken together, we therefore propose computational indicators for screening of anti-estrogenic activities of BPA analogues, which may be beneficial for predicting the estrogenic or anti-estrogenic effects of BPA alternatives.

Screening of Potential PFOS Alternatives To Decrease Liver Bioaccumulation: Experimental and Computational Approaches.

Perfluorooctanesulfonate (PFOS) is a persistent organic pollutant with significant bioaccumulation potential in liver tissues. Exposure to PFOS could cause increase of liver weight, induce adenomas of the liver, and cause hepatomegaly. Alternatives of PFOS might be designed and synthesized that have significantly lower liver bioaccumulation. In this study, we conducted animal exposure experiments to investigate tissue accumulations of 14 per- and polyfluoroalkyl substances. Correlation analysis demonstrated that accumulation of the compounds in rat liver had strong correlations with their binding affinities of liver fatty acid binding protein (LFABP). Thus, we combined a quantitative structure-activity relationship model with molecular dynamics (MD) simulations to develop computational models to predict the LFABP binding affinities of two newly synthesized alternatives, perfluorodecalin-2-sulfonic acid and N-diperfluorobutanoic acid. The binding characteristics of the PFOS alternatives for LFABP were elaborated to explore how the different structural modifications of molecules influenced the underlying binding mechanisms. Subsequent animal experiments demonstrated that the binding free energy calculations based on the MD simulations provided a good indicator to reflect the relative degree of liver accumulation of the PFOS alternatives in the same exposure doses and durations. Our findings from the combination of experimental exposure and computational model can provide helpful information to design potential alternatives of PFOS with weak LFABP binding capability and low liver accumulation.